code: def test_output_orthogonal_pandas():
      X, y = fetch_openml(
          data_id=531,
          return_X_y=True,
          as_frame=False,
          parser="liac-arff",
      )
      df = pd.DataFrame(
          X,
          columns=[
              "crim",
              "zn",
              "indus",
              "chas",
              "nox",
              "rm",
              "age",
              "dis",
              "rad",
              "tax",
              "ptratio",
              "b",
              "lstat",
          ],
      )
      X_fair = InformationFilter(columns=["b", "lstat"]).fit_transform(
          df
      )
      assert all([(c * df["b"]).sum() < 1e-5 for c in X_fair.T])
      assert all([(c * df["lstat"]).sum() < 1e-5 for c in X_fair.T])
  
file_path: scikit-lego/tests/test_preprocessing/test_informationfilter.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.datasets import fetch_openml
  from sklearn.linear_model import LinearRegression
  from sklearn.model_selection import GridSearchCV
  from sklearn.pipeline import Pipeline
  from sklego.common import flatten
  from sklego.preprocessing import InformationFilter
  from tests.conftest import general_checks, nonmeta_checks, select_tests, transformer_checks
label_desc: Use image node_id 6 for calling a global function with example usage: test_output_orthogonal_pandas() without return types